Farasan Island of Saudi Arabia confronts the measurable impacts of global warming in 45 years

Coastal vulnerability assessment is the key to coastal management and sustainable development. Sea level rise (SLR) and anthropogenic activities have triggered more extreme climatic events and made the coastal region vulnerable in recent decades. Many parts of the world also noticed increased sediment deposition, tidal effects, and changes in the shoreline. Farasan Island, located in the south-eastern part of Saudi Arabia, experienced changes in sediment deposition from the Red Sea in recent years. This study used Digital Shoreline Analysis System (DSAS) to delineate the shoreline changes of Farasan Island during 1975–2020. Multi-temporal Landsat data and DSAS were used for shoreline calculation based on endpoint rate (EPR) and linear regression. Results revealed an increase in vegetation area on the island by 17.18 km2 during 1975–1989 and then a decrease by 69.85 km2 during 1990–2020. The built-up land increased by 5.69 km2 over the study period to accommodate the population growth. The annual temperature showed an increase at a rate of 0.196 °C/year. The sea-level rise caused a shift in the island's shoreline and caused a reduction of land by 80.86 km2 during 1975–2020. The highly influenced areas by the environmental changes were the north, central, northwest, southwest, and northeast parts of the island. Urban expansion and sea-level rise gradually influence the island ecosystem, which needs proper attention, management, policies, and awareness planning to protect the environment of Farasan Island. Also, the study’s findings could help develop new strategies and plan climate change adaptation.

www.nature.com/scientificreports/ (USGS) Earth Explorer website (http:// www. earth explo rer. usgs. gov). The data was downloaded from the USGS website with less than 10% cloud cover. The medium-resolution Landsat imageries were widely used for landrelated studies and shoreline sifting analysis in the coastal regions (Fig. 2).
Image pre-processing. The shoreline shift analysis system needs geometric, atmospheric and radiometric correction of the satellite image 33 . The pixel matching is the main condition for pre-processing; otherwise, the change cannot be estimated from the reflectance values 34 . The radiometric correction may include subtraction of atmospheric correction (FLAASH method), view angles and terrain correction, reduction of the calibration and sensor calibration 35 . The atmospheric correction is essential for wavelength-related information. The FLAASH model was used for atmospheric correction, which modifies pixel-based X corresponding to the solar wavelength range 36,37 . The model was used for aerosol/haze removal and clarity of the Landsat imageries. After radiometric correction, Landsat imageries were geometrically corrected. The imageries were included in the World Geodetic System (WGS 1984) datum and Universal Transverse Mercator (UTM) projection system. The tidal information of Farasan Island is around 1.2 m at 4.40 a.m. (high tide) and 0.6 m at 11.02 a.m. (low tide) (https:// www. tides chart. com/ Saudi-Arabia/ Jazan-Region/ Faras an/). The tidal data is not shown in the manuscript because this study used satellite-based high water level data, which also considers the tidal effects.
Image classification and post-classification. LU/LC classification is the key monitoring system for identifying human intervention, extreme environmental conditions and important aspects of earth surface phenomenon 38 . Anthropogenic activities, global climate change, and sea-level rise have made the coastal land of the Farasan Island dynamics. The supervised classification technique with a maximum likelihood algorithm was used for land use/land cover classification 39,40 . ArcGIS 10.6 was used for Landsat data classification for different Figure 1. The location map of the studied Farasan Islands, Saudi Arabia 31,32 . Saudi Arabia boundary data was downloaded from DIVA-GIS website (https:// www. diva-gis. org/). The satellite data was downloaded from USGS earth explorer (https:// earth explo rer. usgs. gov/). The map was generated using ArcGIS software, version 10.6 (https:// suppo rt. esri. com/ zh-cn/ produ cts/ deskt op/ arcgis-deskt op/ arcmap/ 10-6-1). www.nature.com/scientificreports/ years like 1990, 2000, 2010 and 2020. Due to image unavailability and bad image quality, the data for the year 1975 was not classified. The accuracy assessment and kappa coefficient identification of each classified imageries are more useful for monitoring the error matrix for each classified year 41 . The ERDAS Imagine software was used for generating the accuracy assessment and kappa coefficient ( Table 2). The field data and Google Earth data were used for validation and ground referencing. The accuracy assessment and kappa coefficient were calculated using formulas given in Eqs. (1) and (2) where n ij represents the diagonal elements in the error matrix, k is the total number of classes in the land use/land cover classification, n is the total number of samples in the error matrix, and K i represents the kappa coefficient.  Geospatial indices. NDVI. The vegetation index is more useful for monitoring the vegetation condition and change analysis of vegetation area. The Landsat TM and OLI/TIRS data (1990-2020) were used for calculating the vegetation index (NDVI). The vegetation-covered and degradation areas were also identified using NDVI (Eq. 5).
NDBI. The Normalized Difference Built-up Index (NDBI) was calculated for the urban area using Landsat TM and OLI/TIRS data. The shortwave infrared (SWIR) is characteristically higher reflectance compared to the near-infrared region. This built-up index (Eq. 11) is used for built-up area and land use planning 49 : NDBI value ranges between − 1.0 and + 1.0. The positive values of NDBI were considered as the build-up area.
Shoreline extraction technique. Several automatic and semi-automatic techniques have been recently used to extract shorelines from optical satellite imagery. Supervised and unsupervised classifications 20,50-52 , band rationing 22,53 , and threshold values 54,55 are among the most well-known and straightforward methods. The High Water Line (HWL) is generally used to delineate the shoreline shifting from different years' satellite Landsat datasets. HWL is also often used as the identifier 56 for the highest point of the earlier high tide derived from www.nature.com/scientificreports/ remote sensing data and the coast by a perceptible wet/dry strip 1 . The HWL was estimated using band rationing and then digitized in ArcGIS 10.6 software. The employed band rationing of Landsat TM was B5/B2, and Landsat OLI/TIRS was B6/B3. The reclassifications of the calculated bands were used for shoreline change analysis. The values less than 1 denote water pixels, and 0 denotes the land pixels. After reclassification, the raster-tovector conversion and line smoothing technique were used for shoreline extraction.
Baseline creation and laying of transects. After digitizing the shoreline of Farasan Island for different years from 1975 to 2020, all vector lines were clipped to generate a common shapefile. The buffer was created to identify the baseline for calculating the shoreline shifting rate over the period. Transects were created at 500 m intervals for the entire island.
Uncertainty in shoreline shifting. The error in shoreline change analysis was identified using the Landsat dataset 57 and the shoreline shifting statistical significance analysis 58 . Test and train data were used to assess shoreline shifting data, where the test data was field datasets or ground point data. The ground point data were used to generate the error matrix and get the high accuracy of shoreline change analysis.
Transect-from-baseline approach. The Digital Shoreline Analysis System (DSAS) tool derived from the USGS website was used to delineate transect and shoreline change analysis. ArcGIS 10.6 was used to create the transect line for calculating the shoreline shifting each year. The EPR and LRR models were used to analysis of shoreline position changes 59,60 . The DSAS tool 61 was used for this purpose. The EPR and LRR models were used for shoreline change analysis and transect-based land alteration analysis. The End Point Rate (EPR) is calculated by the distance of the total shoreline shift in the different periods between each transect's initial and newest measurement. The equation of EPR calculation is: where, A − B represents the distance of the shoreline in meters and T represents the time between the youngest and oldest shoreline area.
The endpoint rate was calculated for each data pair, like 1975-1990, 1990-2000, 2000-2010 and 2010-2020. The rate was calculated using the distance between two shoreline areas for different intervals 42,77 . The linear regression rate was used to calculate the rate of the entire study area . The LRR method was used to fit the least-squares lines to all shoreline points 63 . The different 4 years of data were used to map and monitor the shoreline change and measure the shoreline change rate.

Application results
Land transformation. Land transformation is the key research topic for monitoring land degradation and earth surface phenomena study. Global warming, climate change, extreme environmental events and urban expansion influence the land transformation worldwide, triggering land losses, vegetation degradation, builtup expansion, infrastructural development, increased heat stress and air pollution. The land transformation study of Farasan Island was necessary to generate land use and land cover-related information and land loss area identification. The global sea-level rise and climate change have increased the vulnerability of shorelines on the Farasan Island 31,64 , figures were generated using ArcGIS software 10.6, https:// www. esri. com/ en-us/ arcgis/ about-arcgis/ overv iew.
Land use and land cover of Farasan Island is mostly affected by the extreme natural environmental condition and sea-level rise. The total area of Farasan Island has been reducing due to sea-level rise and shoreline shifting. Most of the areas are covered by bare land and scrubland, as identified in the study area. Vegetation is the most dominating factor in developing a healthy environment and increasing the air quality in an area. The development of urban expansion causes increased heat stress, oxygen deficiency, land transformation and ecological disturbances. Five types of LU/LC classes were identified in Farasan Island; vegetation, scrub Land, bare land, coastal lowland and built-up land ( Fig. 3a-d). The results revealed an increase in vegetation area over the study period. The notified area of vegetation in different years was 22.74 km 2 (1990), 25.39 km 2 (2000), 35.84 km 2 (2010), and 39.92 km 2 (2020). The vegetation areas were mostly mangroves. Besides, some densely vegetated land was identified in the coastal and some built-up locations. Table 3 shows the areas that belong to different land use and the percentage of each classified area to total area. The scrublands, the dominant land use in the area, showed a gradual increase over time. The area of scrubland in different years were 4.93 km 2 (1990), 8.24 km 2 (2000), 11.25 km 2 (2010), and 23.50 km 2 (2020) and the bare lands were 612.23 km 2 (1990), 597.30 km 2 (2000), 563.47 km 2 (2010), and 542.38 km 2 (2020) ( Table 3).
Coastal lowland is mainly located in the shoreline or coastline area. A significant portion of the study area is the coastal lowland. Its coverage in different years were as follows: 3.69 km 2 (1990), 1.16 km 2 (2000), 1.64 km 2 (2010), and 0.52 km 2 (2020) respectively ( Fig. 4a-e). The coastal lowland gradually decreased due to global climate change-induced sea-level rise. The built-up land increased due to population pressure and infrastructural development. Farasan, Sair, Abu Twoq, Khutob, Qummah, Al Qessar and Al Meharrg are the places where the built-up land has increased simultaneously. Besides, there are many vegetated lands like Al Meharrq, Qandal Forest, Khutob and the northern coastal side in this study area. Table 4 was used to calculate the areal change in land use in different periods on Farasan Island. The vegetation, scrubland, and built-up lands showed an increase, while bare land and coastal lowland showed a decrease due to shoreline shifting, urban expansion and population pressure. The changes in vegetation cover were 2.65 www.nature.com/scientificreports/      www.nature.com/scientificreports/ also triggered land alteration and thermal variation. Therefore LU/LC study and thermal variation investigation are important to protect the environment using novel technologies and adaptation policies.   Shoreline change analysis. Anthropogenic activities, extreme environmental conditions, cyclones, sealevel rise, and tidal effects change the shoreline. The shoreline is important for detecting coastal vulnerability and monitoring global climate change. The present study showed that the shoreline of Farasan Island eroded in some parts and sediment deposition caused accretion in some parts. However, erosion was higher compared to accretion. The upper part of Abu Twoq was mainly eroded due to sea-level rise. Farasan Island experienced a huge amount of sediment deposition. Maximum sediments deposited into the Red Sea region like north of Jizan  Table 9). The upper part of Farasan Island was highly eroded. The upper island was connected with the main island, but after the sea level rose, the area was eroded and submerged in the sea (Fig. 8a-e) 31 Land transformation is a common phenomenon in coastal areas that has been accelerated due to global climate change and human activities. The SLR of the Red Sea has triggered the island's coastal vulnerability, erosion   31,64 . The satellite data was downloaded from USGS earth explorer (https:// earth explo rer. usgs. gov/). The map was generated using ArcGIS software, version 10.6 (https:// suppo rt. esri. com/ zh-cn/ produ cts/ deskt op/ arcgis-deskt op/ arcmap/ 10-6-1).

Discussion
The historical shoreline change is the most important research topic for generating, mapping and monitoring the global sea-level rise and land transformation. Landsat imagery is widely used for generating the high water level area and shoreline shift in the coastal regions. The geomorphological changes are also necessary for identifying coastal management. The present study revealed that sea-level rise and shoreline change in the last decades had influenced Farasan Island. SLR is the most important to identify the shoreline change in the coastal region, where ice melting, climate change, and vegetation damage increased the SLR and the coastal vulnerability and coastal erosion. The erosion rate of Farasan Island gradually increased due to the SLR. Therefore, SLR is one of the triggering factors for shoreline change. Several circular to elliptical diapirs with diameters ranging between 3 and 35 km underlie an uplifted coral reef deposit in the northwest and southeast Farasan Islands 65 . These diapirs cause significant land deformations on the islands 66 . No study has been conducted to assess the role of salt diapirs on shoreline changes on Farahsan Island. A single study conducted on the evaluation of the salt-related land deformation in Jazan city diapir nearly 50 km east of Farahsan island by Pankratz et al. 67 revealed large rates of land deformation in the Jazan diapir. The study showed a rise in diapir's elevation in the center up to 4.7 mm/year while subsiding the low-relief flats by www.nature.com/scientificreports/ − 7.5 mm/year. Although the land deformations due to diapirs are localized, they can affect the shoreline changes in the islands. The present study estimated the shoreline positions from the satellite imageries and extracted the changes due to land deformation by diapirs. The natural resources of the island are very diverse. It has a high economic and recreation value 68 . Ecologically, it is rich with diverse species which need conservation [67][68][69][70][71] . The area is also highly perspective of culture and heritage. A recent study highlighted the significance of Farasan Island for heritage 72 . Therefore, it is important to understand the changes in the islands due to human activities.
The present study revealed that the islands' total land area was 695.22 km 2 in 1975, which was reduced to 614.17 km 2 in 2020. Landsat-8 data for geological mapping of the island were used 73 . The authors estimated the island's total area is 739 km 2 , which is very near to that estimated in this study. Another study was conducted for geomorphological mapping using multi-proxy data 74 . They reported depressions (lowlands) located on plateau surfaces as one of the major formations on the island. The present study also found lowlands as one of the major features of the island. Another study reported an increase in vegetation on the islands 75 . The findings of the present study also collaborate with it. Therefore, it can be remarked the satellite image-based shoreline estimation method used in this study is an effective tool for mapping erosion and accretion in remote and not easily accessible regions like Farasan Island.
The present study revealed both erosion and accretion of the Farasan Islands. There was a spatial variability in accretion and erosion. Overall, 83.99 km 2 of land was lost while 3.13 km 2 was gained during 1975-2020. This indicates a loss of nearly 80 km 2 of land over the study period. Higher loss of land is due to unsustainable human activities and sea-level rise. Due to the SRL, Farasan Island faces huge land alteration along with shoreline mitigation. Also, increased human habits caused land alteration along with the thermal variation in the study area. Climate change is the triggering factor for SLR and human intervention the land alteration like vegetation degradation and built-up expansion. Vegetation degradation also is a triggering factor for shoreline change. Coastal erosion is reduced due to vegetation, but anthropogenic activities reduce the vegetation on Island, causing  31,64 . The satellite data was downloaded from USGS earth explorer (https:// earth explo rer. usgs. gov/). The map was generated using ArcGIS software, version 10.6 (https:// suppo rt. esri. com/ zh-cn/ produ cts/ deskt op/ arcgis-deskt op/ arcmap/ 10-6-1). www.nature.com/scientificreports/ increased shoreline change. The shoreline was a noticeable change during the study period from 1975, but the anthropogenic activities stated in the most recent time. Therefore anthropogenic activities are not the only triggering factor for shoreline change. Climate change-induced SRL is also a main major cause of shoreline change.
The population of Farasan has increased significantly in the last decades. Economic activities are also accelerated in the region. The government planned many development activities in the islands, namely terminal, marina, hotel, cultural and environment administration, and retail. Besides, a harbour is planned to connect the island with the other globally important cities in the region. Increased population and development activities have made this ecologically rich region vulnerable 76 . However, some studies show no changes in some species. For example, Hausmann and Meredith-Williams 30 showed no change in shell middens distribution on the island despite adverse climatic conditions. Another investigation reported a decrease in mountain gazelle in some islands in the Farasan 76 .
Besides human interventions, rising sea levels due to global warming also affected the Farasan Islands. The fluvial deposits from the wadis during the Holocene period formed the Red Sea coastal plain in the Farasan region. An examination of the island's geological structure using existing well log data 66 revealed the stratigraphic succession of the islands as sand, coral reef limestone, marly limestone, shale, and evaporite, from top to bottom. The sandy deposition at the top has made the island more vulnerable to sea-level rise.
The surface elevation of the Red Sea is significantly influenced by water balance in winter. Therefore, it has significant seasonal variability in sea level. Global climate change has made the situation more severe. Besides, there is a unidirectional increase in sea level. Alawad et al. 77 reported an increasing trend in the sea level of the Red Sea by about 0.28 cm/year during 1993-2010, which was very near to the global average. The present study revealed that increased sea level might be another cause of decreasing area of the Farasan Islands. An analysis of the trends in extreme waves near the shore showed an increase in the 95th and 99th percentile extreme waves 78 . The increase in extreme waves can also cause increased erosion in the islands.  31,64 . The satellite data was downloaded from USGS earth explorer (https:// earth explo rer. usgs. gov/). The map was generated using ArcGIS software, version 10.6 (https:// suppo rt. esri. com/ zh-cn/ produ cts/ deskt op/ arcgis-deskt op/ arcmap/ 10-6-1).

Conclusion
Shoreline shift analysis is the key to understand the erosion and accretion in the coastal areas. Global sea-level rise, extreme environmental events, and anthropogenic activities have triggered coastal vulnerability, influencing human habited, ecological diversity, and environmental conditions. Farasan Island is located in the southern part of the Red Sea, around 40 km from Jazan city. It is the habitat of many species and mangroves. Therefore, it is important from an ecological point of view. Sea-level rise and sediment dynamics caused a shift in the island's shoreline. The present study revealed that climate change had accelerated shoreline shift, which influenced the local environmental condition, misbalances of biodiversity and areal change. The study revealed a spatial variability of erosion and accretion, which caused erosion of 83.99 km 2 of the land while accretion of only 3.13 km 2 during 1975-2020. This indicates a loss of nearly 80 km 2 of the island's land over the study period. Nearly 1975-1990, 54.18 km 2 of the shoreline was shifted (eroded) during 1975-1990, mostly in the northeast, north, east, and southwest. In contrast, only 4.66 km 2 of the area was increased through accretion. Erosions and accretions were 10.97 km 2 and 1.03 km 2 during 1990-2000, although 19.23 km 2 and 1.19 km 2 during 2000-2010. The least shift in shoreline was during 2010-2020, with 2.37 km 2 accretion and 6.46 km 2 erosion. The shoreline shifting was more prominent in the study area's northeast, central and southern parts. Shoreline change information provided in this paper can be helpful for the research community in understanding coastal vulnerability and global climate change-related information. Decision-makers, administrative departments, and other stakeholders can adopt strategies for coastal management and sustainable development in Farasan Island based on the study's findings. Further analysis can be conducted in the future to quantify the effects of different factors on shoreline changes. A hydro-dynamic model can be used to assess the changes in sea waves due to global warming and their impacts on accretion and erosion.

Data availability
The data used in the research modelling are freely available satellite data mentioned within the manuscript. The satellite data was downloaded from USGS earth explorer (https:// earth explo rer. usgs. gov/). The map was generated using ArcGIS software, version 10.6 (https:// suppo rt. esri. com/ zhcn/ produ cts/ deskt op/ arcgis-deskt op/ arcmap/ 10-6-1).